Empowering fall webworm surveillance with mobile phone-based community monitoring: a case study in northern China

Abstract

Recent advances in information and communication technologies, such as mobile Internet and smartphones, have created new paradigms for participatory environment monitoring. The ubiquitous mobile phones with capabilities such as a global positioning system, camera, and network access, offer opportunities to establish distributed monitoring networks that can perform a wide range of measurements for a landscape. This study examined the potential of mobile phone-based community monitoring of fall webworm (Hyphantria cunea Drury). We built a prototype of a participatory fall webworm monitoring system based on mobile devices that streamlined data collection, transmission, and visualization. We also assessed the accuracy and reliability of the data collected by the local community. The system performance was evaluated at the Ziya commune of Tianjin municipality in northern China, where fall webworm infestation has occurred. The local community provided data with accuracy comparable to expert measurements (Willmott’s index of agreement >0.85). Measurements by the local community effectively complemented remote sensing images in both temporal and spatial resolution.

Keywords

Forest pest monitoring / Mobile phone / Community monitoring / Hyphantria cunea Drury / Field survey

References

[1] Danielsen F, Skutsch M, Burgess ND, Jensen PM, Andrianandrasana H, Karky B, Lewis R, Lovett JC, Massao J, Ngaga Y. At the heart of REDD+: a role for local people in monitoring forests?. Conserv Lett, 2011, 4(2): 158-167.

[2] Evans K, Guariguata MR (2008) Participatory monitoring in tropical forest management: a review of tools, concepts and lessons learned. Center for International Forestry Research (CIFOR), Bogor, Indonesia

[3] Ferster CJ, Coops NC. A review of earth observation using mobile personal communication devices. Comput Geosci, 2013, 51: 339-349.

[4] Itô Y, Miyashita K. Biology ofHyphantria cunea Drury (Lepidoptera: Arctiidae) in Japan. V. Preliminary life tables and mortality data in urban areas. Res Popul Ecol, 1968, 10(2): 177-209.

[5] Kanhere S. Hota C, Srimani P. Participatory sensing: crowdsourcing data from mobile smartphones in urban spaces. Distributed computing and internet technology. 2013, Berlin: Springer, 19 26

[6] Kelly NM, Tuxen K. WebGIS for monitoring “Sudden Oak Death” in coastal California. Comput Environ Urban Syst, 2003, 27(5): 527-547.

[7] Kennedy R, Mcleman R, Sawada M, Smigielski J. Use of smartphone technology for small-scale silviculture: a test of low-cost technology in Eastern Ontario. Small-scale For, 2014, 13(1): 101-115.

[8] Larrazabal A, Mccall MK, Mwampamba TH, Skutsch M. The role of community carbon monitoring for REDD+: a review of experiences. Curr Opin Environ Sustain, 2012, 4(6): 707-716.

[9] Li SM, Saborowski J, Nieschulze J, Li ZY, Lu YC, Chen EX. Web service based spatial forest information system using an open source software approach. J For Res, 2007, 18(2): 85-90.

[10] Sader SA, Ross K, Reed FC. Pingree forest partnership: monitoring easements at the landscape level. J For, 2002, 100(3): 20-25.

[11] Stuart-Hill G, Diggle R, Munali B, Tagg J, Ward D. The event book system: a community-based natural resource monitoring system from Namibia. Biodivers Conserv, 2005, 14(11): 2611-2631.

[12] Su MW, Fang YL, Tao WQ, Yan GZ, Ma W, Zhang ZN. Identification and field evaluation of the sex pheromone of an invasive pest, the fall webworm Hyphantria cunea in China. Chin Sci Bull, 2008, 53(4): 555-560.

[13] Whitelaw G, Vaughan H, Craig B, Atkinson D. Establishing the Canadian community monitoring network. Environ Monit Assess, 2003, 88(1–3): 409-418.

[14] Willmott CJ. On the validation of models. Phys Geogr, 1981, 2(2): 184-194.

[15] Yang ZQ, Wei JR, Wang XY. Mass rearing and augmentative releases of the native parasitoid Chouioia cunea for biological control of the introduced fall webworm Hyphantria cunea in China. Biocontrol, 2006, 51(4): 401-418.